5 Ways Artificial Intelligence Can Boost Productivity in Sales Ops

Your sales ops team is working hard to uncover trends and provide compelling ideas, tools, and processes to the sales team. Let artificial intelligence take some of the manual work out of it and watch your productivity soar.

Artificial Intelligence (AI) isn’t just a buzzword in the data world. When used correctly, it will save you time, which frees up your team to execute on strategic sales initiatives empower the sales team.

AI is growing increasingly prevalent in organizations large and small. According to Adobe, only 15% of enterprises are using AI as of today, but 31% are expected to add it over the coming 12 months. Adobe also discovered that 47% of digitally mature organizations have a defined AI strategy. You can read more about trends in AI here . This means that more and more leaders are embracing the power of AI.

What Is AI and How Is It Used?

AI, often referred to as machine learning, allows computer systems to gather and store information through learning algorithms, and then deploy the knowledge to accomplish tasks that would normally be done by a human.

A great example of successful implementation of AI is Expensify’s use of Concierge, the friendly virtual assistant who helps you remember to submit your business expenses and make your life easier. Not only has Concierge learned how to handle a variety of support issues, but she gathers data on every expense reported in the system, and can knows the real-time pricing of every flight, hotel, and car rental. Over time, Concierge tracks your habits and learns more about how to customize your experience. Expensify has embraced the AI technology and it is paying off in a big way. Read more about Expensify’s journey into the world of AI here .

Data is a valuable asset to an organization. However, a challenge faced by many Sales Ops leaders is how to make the most of your data to drive value. Years of entering and storing data means that you now have a sea of data from different sources, and inefficient methods to analyze it. Often, the answer to this is a large, drawn out data project that seems daunting from the start. The data you have may be scattered in different sources throughout the organization, data integrity may not be strictly enforced, data could be updated infrequently or even missing all together. However, this data is the key to deriving insights about customers and empowering the sales team.

As a Sales Ops leader, you need to define your objectives and processes and then determine how to leverage data.

Download the AI Implementation Checklist to find out if AI is right for your organization, leverage a checklist to determine if your organization would benefit from AI, and leverage a checklist to determine if your organization is set up for AI.

The Benefits of Using AI

There are many benefits to AI, so consider how AI could assist as you embark on any large-scale data project:

Use AI to Reduce Time Spent Manually Cleaning Data

Imagine you are ready to embark on a large-scale data analytics project, only to uncover inconsistency after inconsistency. Perhaps there are missing fields or Null values. Maybe certain data dimensions contain no unique identifier for a record.

A common woe in email address storage is spelling errors or improper formatting. Great insights start with data you can trust. The first step is cleaning your data; however, data cleaning projects are usually trial and error and very time consuming. AI can help lessen this workload by using a learning model to match new data to existing data in the system. The more trials the algorithm goes through, the more accurate it becomes.

AI Can Help Expand Your Data Sources Beyond Your Organization Data

If the goal is to mine your data set for information, the first step is to build a data set that is rich with many metrics and factors. To do this, your organization will need to look beyond the CRM and ERP data you already have and explore untapped data sources such as social media data and google analytics to provide metrics on website traffic and customer sentiments.

Even Google itself uses AI in determining trending topics from around the web. AI is used in web browser search results to analyze a user’s search history and browsing patters. The algorithm can then aggregate this data from all over the world and look for common words used in searches. Learn more about how AI can help your organization explore data here.

Bad Data Can Thwart Plans for Data Projects, Use AI to Keep It Consistent

AI can improve data quality and accuracy by automatically identifying duplicates and detecting anomalies in the data. If lack of consistent data entry routine is a problem you face in your CRM, AI can assist by predicting data entry patterns from CRM users and automatically capturing data from sources such as email and Excel. Even if you have near-perfect CRM data and consistent data entry procedures, your own data will only take you so far.

AI can help you integrate your data with third party sources, which can help unlock a new box of insights to explore. Learn more about using AI to improve your data quality here.

AI Can Help Predict and Model Sales Performance Better Than Ever Before

AI can find trends and patterns in the data by analyzing existing data as it relates to competition, deal size, timing, and several other factors. This in turn can help you predict performance by using an algorithm to model the outcome of an opportunity based on these factors. Along those same lines, AI can track trends in the key customer behaviors and automatically update dashboards that are aligned to provide some insights that advance your strategy.

Don’t Rely on AI Alone, Integrate It with the Business Intelligence (BI) Tools You Already Use

AI and BI should be used to compliment each other, rather than one as a substitute for the other. BI tools will tell you information about what has already happened, such as past sales performance. AI tools help you predict what happens next.

Do some research on the BI tools you are currently using in your organization, and spend time understanding what works and what doesn’t. Talk to your team about the challenges they are facing and ask around your network for some ideas of what has worked in other organizations. If you are not currently employing business intelligence tools, now is a great time to get started. There is no shortage of BI tools on the market, but it is important to find the right ones for your needs.

Some examples of powerful tools are Alteryx and Tableau which are easy to learn and have hundreds of features to help wrangle your data and produce impactful reports. If budget is an issue, there are plenty of free open-source options as well. Postgres is a great option for data warehouses, and Knime is a great ETL and reporting tool. The R language is relatively quick to learn and RStudio has many packages that are open source as well. Empower your team to make the most of the tools available to them to better understand the market.

Your data is a valuable asset to your organization; however, it is also the source of many pain points. The good news is that the data analytics field is full of the latest and greats tools and methods to help you make the most of your valuable data. The solution to your problem is out there, and when implemented correctly with the right knowledge and support, you will find that your sales operations can be more targeted, focused, and productive than ever before. This will, in turn, help empower the sales team to drive revenue across the organization.

Download the AI Implementation Checklist to find out if AI is right for your organization, leverage a checklist to determine if your organization would benefit from AI, and leverage a checklist to determine if your organization is set up for AI.

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Malorie Feidner

Malorie uses an analytical approach to identify solutions to complex organizational challenges. She is passionate about interpreting data and promoting business intelligence for clients. Malorie asks the right questions to discover insights that help clients achieve their objectives. Her educational background in engineering and data analytics provide the technical acumen needed to examine a situation, offer recommendations and implement solutions that drive success. She has delivered impactful results for several fortune 500 companies in the areas of: asset valuation, merger & acquisition financial analysis, IT project management, and operational process optimization.